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一种自抗扰控制器参数的学习算法

武雷 保宏 杜敬利 王从思

武雷, 保宏, 杜敬利, 王从思. 一种自抗扰控制器参数的学习算法. 自动化学报, 2014, 40(3): 556-560. doi: 10.3724/SP.J.1004.2014.00556
引用本文: 武雷, 保宏, 杜敬利, 王从思. 一种自抗扰控制器参数的学习算法. 自动化学报, 2014, 40(3): 556-560. doi: 10.3724/SP.J.1004.2014.00556
WU Lei, BAO Hong, DU Jing-Li, WANG Cong-Si. A Learning Algorithm for Parameters of Automatic Disturbances Rejection Controller. ACTA AUTOMATICA SINICA, 2014, 40(3): 556-560. doi: 10.3724/SP.J.1004.2014.00556
Citation: WU Lei, BAO Hong, DU Jing-Li, WANG Cong-Si. A Learning Algorithm for Parameters of Automatic Disturbances Rejection Controller. ACTA AUTOMATICA SINICA, 2014, 40(3): 556-560. doi: 10.3724/SP.J.1004.2014.00556

一种自抗扰控制器参数的学习算法

doi: 10.3724/SP.J.1004.2014.00556
基金项目: 

国家自然科学基金(50775170,51105290,51035006,50805111,51175398)资助

详细信息
    作者简介:

    保宏 西安电子科技大学电子装备结构教育部重点实验室教授. 主要研究方向为天线结构的分析、优化与控制.E-mail:baohong029@gmail.com

A Learning Algorithm for Parameters of Automatic Disturbances Rejection Controller

Funds: 

Supported by National Natural Science Foundation of China (50775170, 51105290, 51035006, 50805111, 51175398)

  • 摘要: 针对自抗扰控制器(Automatic disturbance rejection controller,ADRC)参数多且耦合性强,参数难于被确定的问题,提出了一种ADRC参数的自动调整算法. 该算法以构造的控制性能函数为学习目标,根据参数对性能指标的影响,通过惩罚函数在线不断更新参数在有界区间内的概率密度分布,使得控制参数最优值的概率密度值最大. 通过开环不稳定系统算例和对工业机电驱动器单元(Industrial mechatronic drives unit,IMDU)的控制实验,仿真和实验结果证明了该算法的有效性.
  • [1] Han Jing-Qing. A new type of controller: NLPID. Control and Decision, 1994, 9(6): 403-407(韩京清. 一种新型控制器 --NLPID. 控制与决策, 1994, 9(6): 403-407)
    [2] Han Jing-Qing. Nonlinear state error feedback control law --NLSEF. Control and Decision, 1995, 10(3): 221-225(韩京清. 非线性状态误差反馈控制律--NLSEF. 控制与决策, 1995, 10(3): 221-225)
    [3] Han Jing-Qing. Auto-disturbances-rejection controller and its applications. Control and Decision, 1998, 13(1): 19-23(韩京清. 自抗扰控制器及其应用. 控制与决策, 1998, 13(1): 19-23)
    [4] Han Jing-Qing. From PID to active disturbance rejection control. IEEE Transactions on Industrial Electronics, 2009, 56(3): 900-906
    [5] Wang Shun-Huang, Li Xiao-Tian, Zheng Qiu-Bao, Zheng Bao-Yuan, Deng Rui-Lan, Hu Yi-Shun. Nonlinear PID algorithm and its application in distributed system of the electronic heating furnace. Acta Automatica Sinica, 1995, 21(6): 675-680(王顺晃, 李晓天, 郑秋宝, 郑保元, 邓芮岚, 轷一顺. 非线性PID算法及其在电加热炉集散控制系统中的应用. 自动化学报, 1995, 21(6): 675-680)
    [6] Hou Y, Gao Z Q, Jiang F, Boulter B T. Active disturbance rejection control for web tension regulation. In: Proceedings of the 40th IEEE Conference on Decision and Control. Orlando, USA: IEEE, 2001. 4974-4979
    [7] Wu Dan, Wang Xian-Kui, Zhao Tong, Lv Wei-Long. Application of active disturbance rejection to tracking control of a fast tool servo system. In: Proceedings of the 2005 IEEE International Conference on Control Application. Toronto, Canada: IEEE, 2005. 547-552
    [8] Zhang Rong. An economic interpretation of ADRC. In: Proceedings of the 2011 Chinese Control and Decision Conference. Mianyang, China: IEEE, 2011. 2731-2735
    [9] Talole S E, Kolhe J P, Phadke S B. Extended-state-observer-based control of flexible-joint system with experimental validation. IEEE Transactions on Industrial Electronics, 2010, 57(4): 1411-1419
    [10] Li Xing-Hua, Chen Wen-Lei. Application of active disturbance rejection controller for high precision servo system. In: Proceedings of International Conference on Mechatronic Science, Electric Engineering and Computer. Jilin, China: IEEE, 2011. 2467-2470
    [11] Zhao Yang, Zhao Zhi-Gang, Zhao Bao-Shan, Li Wen-Bo. Active disturbance rejection control for manipulator flexible joint with dynamic friction and uncertainties compensation. In: Proceedings of the 4th International Symposium on Computational Intelligence and Design. Hangzhou, China: IEEE, 2011. 248-251
    [12] Sun Bao-Sheng, Gao Zhi-Qiang. A DSP-based active disturbance rejection control design for a 1-kW H-bridge DC-DC power converters. IEEE Transactions on Industrial Electronics, 2005, 52(5): 1271-1277
    [13] Zheng Qing, Gao L Q, Gao Zhi-Qiang. On validation of extended state observer through analysis and experimentation. Journal of Dynamic Systems, Measurement, and Control, 2012, 134(2): 024505.1-024505.6
    [14] Liu Chun-Fang, Zang Bin. Application and the parameter tuning of ADRC based on CPSO. In: Proceedings of 24th Chinese Control and Decision Conference. Taiyuan, China: IEEE, 2012. 3277-3281
    [15] Howell M N, Frost G P, Gordon T J, Wu Q H. Continuous action reinforcement learning applied to vehicle suspension control. Mechatronics, 1997, 7(3): 263-276
    [16] Mohammadi S M A, Gharaveisi A A, Mashinchi M R, Rafiei S M R. New evolutionary methods for optimal design of PID controllers for AVR system. In: Proceedings of 2009 IEEE Bucharest Power Tech Conference. Bucharest, Romania: IEEE, 2009. 1-8
    [17] Gurz{i P, Steenhaut K, Now{e A, Vrancx P. Learning a pricing strategy in multi-domain DWDM networks. In: Proceedings of 2011 18th IEEE Workshop on Local & Metropolitan Area Networks. Chapel Hill, USA: IEEE, 2011. 1-6
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出版历程
  • 收稿日期:  2012-08-22
  • 修回日期:  2013-03-04
  • 刊出日期:  2014-03-20

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